Edward Capriolo

When we get new servers in I also make a mental note to myself to work twice as hard during the week. You may ask why? The answer is if I can get the machines prepped before they are needed in production it gives me the chance to run Cassandra and the Yahoo Cloud Serving Benchmark on them.

What do you get when you cross, Apache Cassandra, solid state disks, a blade center loaded with 14 blades?.....

In this previous post we ran a benchmark against 8 server class machines with scsi disks. This time we have 14 blades, 32 GB RAM with SSDs! Ow it's on. It's on.

Last time, I did a lot of manual editing of the ycsb load testing scripts. This time I introduced some variables into the scripts that can be set from the command line. Which make it much easier to run the scripts on N machines without having to tweak them individually.

First, lets get this out of the way. This is BigData, not tiny little baby data. We are not inserting 1,000,000 rows. Because if the data fits in one machines main memory, its not BigData!

We are inserting 75,000,000 entries, which turns out to be 322 GB data (~23 GB node with replication factor 3) Now, our machines do have a good amount of RAM (32Gb), and the JVM is sized to 8GB for this test. (I need to make another test with about double the data so I can stress out the SSD drives more.

I actually need to revisit this test. I foo bared it a bit and launched 2 or 3 extra instances. In any case, I saw peaks of nearly 20,000 ops/ sec. I was impressed by this anyway, it took netflix 300 machines from amazons cloud to hit 1,000,000 inserts a second. My 14 node cluster hit was running 7 YCSB instances at once. I achieved 140,000 inserts per second without really trying to hard. I could say more about cloud vs bare metal but I would be digressing.

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